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• Transcriptomic Analysis of HIV-Infected Cells

  Defining the attributes of rare CD4 T cells that harbor latent HIV under therapy with anti-retroviral agents has been challenging due to difficulties in identifying and isolating these cells. These cells represent an important barrier to cure, and characterizing them would aid the design and development of novel HIV cure strategies. In this study, we addressed this challenge using a custom microfluidic technology named Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) that isolates HIV-infected cell transcriptomes, based on HIV DNA detection. We applied this method to HIV DNA+ memory CD4 T cells isolated from blood from five persons with HIV who were receiving anti-retroviral agents. After curating samples based on data quality, we proceeded with bioinformatics analysis from three persons. This analysis identified six transcriptomic pathways that were inhibited in HIV DNA+ cells compared to HIV DNA- cells. These included death receptor signaling, necroptosis signaling, and anti-proliferative G-alpha12/13 signaling. Furthermore, we identified two gene clusters, including 60 and 85 genes, that were significantly associated with HIV DNA+ cells identified by co-expression network analysis. These genes included negative regulators of HIV transcription that were higher in HIV DNA+ cells, positive regulators of HIV transcription that were lower in HIV DNA+ cells, and other genes involved in the negative regulation of mRNA translation, additional RNA processing functions, and the regulation of cellular state and fate. We further examined these signatures in transcriptomic data from CD4 T cell subsets sorted by flow cytometry from nine persons with HIV. We found a partial similarity between the smaller cluster of genes and the signature of CCR6- peripheral TFH cells. Raw sequencing data from all eleven human participant samples included in the study are available. These include samples from two participants who were studied only by FIND-seq, three participants who were studied by both FIND-seq and flow cytometry and six participants who were studied only by flow cytometry.

  Study phs003095

• Neversmoker lung adenocarcinoma

  Non-small cell lung cancer whole genome sequencing We performed whole genome sequencing of Korean never-smoker lung adenocarcinoma patients to discover novel pathway except EGFR and ALK patients. We identified estrogen signaling as a novel enriched signaling. Lastly we validated the elevated estrogen signaling through immunohistochemistry experiment in some patients which increased signaling.

  Study EGAS50000000232

• Solution-based exome capture and HiSeq2000-based massively parallel sequencing of Follicular Lymphoma

  A cohort of follicular lymphoma cases had tumor cells purified from tissue samples after informed consent using flow cytometry. DNA was extracted from the cells, and samples were subjected to solution-based exome capture using the Illumina TruSeq Exome Enrichment Kit and the Illumina HiSeq 2000 platform.

  Study phs000729

• Myocardial Applied Genomics Network (MAGNet) Study

  The MAGNet repository includes non-failing samples from organ donors with no history of heart failure and failing samples from explanted hearts of donors receiving a heart transplant. The study protocol was approved by the Institutional Review Board at the University of Pennsylvania, and all patients provided written informed consent to participate.

  Study phs001539

• Neoantigen Landscape in a Hypermutated Glioblastoma Arising in a Patient with Germline POLE Deficiency Treated with Checkpoint Blockade Immunotherapy

  Whole genome and exome-based DNA sequencing of germline and tumor specimens from serial samples of patients with glioblastoma. The data set includes several metastases and recurrences from a patient with germline POLE-deficiency. The data reveal extensive tumor heterogeneity, clonal evolution, and genomic responses to immunotherapy.

  Study phs001663

• Exome Sequencing of Clear Cell Endometrial Tumors and Paired Non-tumor Samples

  The purpose of this study was to identify somatic (tumor-specific) mutations in clear cell endometrial tumor exomes. The dataset was generated at the NIH Intramural Sequencing Center (NISC) and NHGRI by next generation sequencing the exomes of 16 de-identified primary tumor DNAs and matched non-tumor DNAs.

  Study phs000967

• Analysis of Cell-Free DNA to Predict Outcome to Bevacizumab Combination Therapy in Metastatic Colorectal Cancer Patients

  This dataset includes FASTQ files of low coverage whole genome sequencing of normal tissue (n = 8), tumor tissue (n = 55) and cell free DNA from plasma samples (n=101) from patients with metastatic colorectal cancer treated with bevacizumab. A total of 164 samples are present from two different cohorts. The first batch of samples (n = 139, sample names sAPD302T until sAPD502_P0) were collected from the AC-Angiopredict Phase 2 trial (NCT01822444), the second batch of samples (n = 25m, sample names sAPD503_P0 until sAPD527_P0) were collected from the UMM cohort.

  Dataset EGAD50000000176

• Epigenomic timecourse of brain organoid development

  Single-cell Cut&Tag of three histone modifications and chromatin accessibility over a timecourse of brain organoid development from pluripotency. We profiled 5 time points of brain organoid development and 2 time points of retinal organoid development. At each time point used scCut&Tag to profile histone modifications (H3K27me3, H3K27ac, H3K4me3) as well as multiome-seq (10X) to jointly profile transcriptome and chromatin accessibility from the same cell suspension. Library preparation was carried out with the 10x genomics platform.

  Dataset EGAD50000000222

• Duplex sequencing of selected breast cancer patients

  This study assessed the variant profiles of 22 samples from 11 breast cancer patients with adverse survival outcomes, including paired uninvolved mammary gland samples collected at various distances from primary lesions. Ultra-deep sequencing was performed to identify the presence of low-frequency pathogenic post-zygotic variants in PIK3CA and TP53 genes.

  Study EGAS50000000538